The way optical networks are used is undergoing significant change, driven in part by the huge growth of traffic such as multimedia services and by the increased uncertainty in predicting the sources of this traffic due to the ever changing models of content providers over the Internet. Sophisticated modulation schemes for higher bandwidth 100 Gb/s services and beyond are known and come into commercial use in optical networks of large and increasing link and node numbers.
A bottleneck to widespread deployment of such schemes is the “fixed” wavelength grid approach specified by the International Telecommunication Union (ITU), in which the relevant optical spectrum range in the C-band is divided into fixed-sized spectrum slots. As used herein, a “slot”, “wavelength” or “channel” is defined as a wavelength or a spectrum of wavelengths associated with a certain signal size. A connection is made by assigning spectral (i.e. wavelength) slots on the optical links comprising the path between source and destination. A problem arises with bit rates greater than 100 Gb/s, which occupy spectral widths too broad to fit into such fixed-sized spectrum slots or channels; forcing to fit by adopting higher spectral-efficiency modulation methods which tend to compromise transmission distances. It seems clear that this decade-old ITU “fixed grid” approach will not work for bit rates significantly greater than 100 Gb/s (e.g. 400 Gb/s and above), highlighting the need for a more flexible approach to be developed. Work on such a new “elastic optical networking” approach is underway, based on a “flexgrid” WDM (wavelength division multiplexing) approach, in which the optical spectrum can be divided up in a way to form spectral slots of arbitrary widths which are selectable depending on, e.g., the bit rates being used, tailored to the requirements of the optical transceiver and accommodating new bit rate services.
Representations of the fixed and flexible grid approaches are depicted in the example graphs shown in FIG. 1, in which graphs (a), (c) and (d) depict examples of fixed grid implementations, while (b) and (e) illustrate the flexgrid approach. Graph (a) illustrates the strict guard bands partitioning adjoining optical channels in a fixed grid implementation, and demands or wavelengths at a particular bit rate. Graph (b) shows how the channels for the demand can be grouped into a single “superchannel” which can be transported as one entity in a flexgrid system. In graph (c), five demands (of varying bit rates and distances) and their spectrum needs are shown on a fixed grid, assuming quaternary phase shift keying (QPSK) modulation. Graph (d) depicts the same service demands of graph (c), with adaptive modulation optimized for the required bit rate and reach. Arbitrary-size spectrum slot allocation is shown in the flexgrid implementation of graph (e) which has the same demands as graphs (c) and (d).
In brief, there is typically only one way in fixed grid networks to implement a given demand as the wavelength bit rate, optical reach, and spectrum parameters are highly constrained in their allowable implementation solutions so as to ultimately align with the fixed grid architecture. This means that the demand can occupy less than a full slot resulting in wasted spectrum capacity like that shown in graph (c). On the other hand, a superchannel width wider than the fixed slot width as illustrated in (b) cannot be accommodated in a fixed grid network. In the flexgrid scheme, a choice can be made when implementing a demand, by assigning a modulation format that gives sufficient performance to reach the required distance, while relaxing the requirements on the actual width of the spectral bandwidth occupied by the optical path. The spectrum savings that may be achieved using a flexgrid approach may be seen by a comparison between the fixed grid scheme shown in (d) and an identical scenario when used under the flexgrid scheme shown in (e). In other words, moving away from the use of fixed-position guard bands defining channel widths in the fixed grid approach, can achieve efficiencies by spacing channels contiguously or at least closer to each other, across the spectrum. This can result in the freeing up of spectrum resource for other demands. In this way, the flexgrid scheme allows greater flexibility and choice in allocating spectrum.
A drawback suffered particularly by flexgrid systems, however, is that the optical spectrum can become “fragmented”, consisting of non-contiguous used spectrum sections in a manner akin to a computer hard disk including fragmented disk blocks. This is because when a signal or demand reaches its destination node, the optical connection terminates and the wavelength or channel “vacates” the spectrum slot. One way of preventing spectrum fragmentation is to find a new resource request having an identical or near-identical slot width, to occupy that slot just at the point when the slot becomes available. The chances of such coincidences occurring are, however, not high, and as may be expected, such vacated slots are likely to remain wholly or partly unfilled. In other words, even if a wavelength channel is found which is capable of fitting into the vacated slot, this is likely to be narrower in width to the previous wavelength channel, resulting in the creation of unused sections of the spectrum so that the level of fragmentation tends to increase over time. The state in which a spectrum comprises non-contiguous used or unused sections results in a state of “entropy” (randomness or disorder). Matters become especially problematic when the unused spectrum parts are so narrowly splintered that they cannot be used to accommodate a demand, even when the total (summed) amount of actual unused spectrum might otherwise have been usable. By way of illustration, graph (e) of FIG. 1 depicts an optimal situation in a flexgrid environment, in which the demands essentially occupy contiguous positions in the spectrum. In a less ideal case, fragments of unused “stranded” spectrum fragments can be represented as gaps between neighboring used slots, as shown in, e.g., FIG. 3 (discussed below). It can be expected that failure to address this problem may eventually result in significant inefficiencies in the use of the precious spectrum resource, possibly resulting in the need to build expensive new links to cope with traffic levels.
As might be expected, this is much less of a problem in fixed grid systems owing to the standardized slot size arranged contiguously to each other. Indeed, splintering of the spectrum is simply not an issue in a fixed grid system, since all slots are of the same standard size, such that when a channel is terminated and frees up spectral space, then any new demand that arises will automatically be of the same (standardized) width to fit into the available slot.
There is therefore a need to address the above issues, especially in connection with the routing of optical data traffic in flexgrid implementations in the elastic optical networking paradigm.
Some approaches referring to an entropy measure along optical links are known. For example, “Utilization Entropy for Assessing Resource Fragmentation in Optical Networks” (W. Xi et al., Optical Fiber Communication Conference, OSA Technical Digest (Optical Society of America, 2012)) discusses spectral fragmentation using qualitative and algorithmic descriptions, which as an approach may not provide a predictive measure of the overall spectral fragmentation. This is because algorithmic approaches often implies a degree of non-linearity (e.g. the presence of binary logic steps, i.e. XOR, OR, AND operations etc.), which may cause non-monotonic (and/or non-linear) behavior of the output result of the algorithm. Nor does an algorithm necessarily offer the degree of ‘sensitivity’ or ability to distinguish between subtle differences of fragmentation—it depends on the construction of the algorithm, and its quantitative behavior. Methods based on this approach might not be sufficiently reliable for deployment in the field.
Another document titled “Planning and Provisioning of Elastic O-OFDM Networks with Fragmentation-Aware Routing and Spectrum Assignment (RSA) Algorithms” (M. Zhang et al., Asia Communications and Photonics Conference, OSA Technical Digest (online) (Optical Society of America, 2012)) describes a fragmentation-aware RSA, which uses a fragmentation ratio when making resource allocations. It does not however use an entropy-based metric for choosing routes, and the paper explicitly notes that the utilization entropy approach of the W. Xi document above does not sufficiently quantify bandwidth fragmentation to be helpful.
“Dynamic Routing and Frequency Slot Assignment for Elastic Optical Path Networks that Adopt Distance Adaptive Modulation” (T. Takagi et al., Optical Fiber Communication Conference/National Fiber Optic Engineers Conference 2011, OSA Technical Digest (CD) (Optical Society of America, 2011)) describes a classical style RSA applied to elastic networks and does not take into account spectrum entropy.
As such, the idea of assessing resource fragmentation and fragmentation-aware routing are known, as is the application of entropic concepts in the area of optical fiber spectrum. However, a stochastically well-ordered study of optical networking on statistical mechanical principals using information-theoretic definitions of entropy has not yet been known to have been conducted in connection with optical networks, whose size with their ever-larger link and node numbers, and featuring an ever-increasingly exploitable optical spectrum (atomized to an ever-smaller quantum, 100 GHz→6.25 GHz) now makes them particularly amenable to such statistical mechanical (thermodynamical) analyses. In particular, there is currently no known approach which allows calculation of an entropy measure in manner which is essentially quantitative in behavior, (i.e. it can be expressed as a compact mathematical equation) which has highly predictive behavior, is monotonic as a measure of entropy, and can sensitively distinguish between arbitrarily fine differences of fragmentation. There is also no method allowing for such a measure to be used in an optical path routing choice in a manner which allows overall network resource (i.e., utilization of overall network capacity) to be more greatly exploited before overall networking blocking probabilities start exceeding certain thresholds (e.g. at 5%). In particular, it would be useful to reduce or stop the spectrum becoming fragmented in the first place. With the aim of full and efficient use of the spectrum resource, network operators would wish to have tools to address the above problems.